Network data analysis has generally been utilized for identifying information associated with networks. Oftentimes, network systems performing such analysis are designed to analyze all data communicated over an associated network. For example, the network systems have traditionally performed the analysis of network data in order to ensure the security, reliability, and speed of networks. However, conventional systems utilized for performing network data analysis have exhibited various limitations, such as, for example, when a significant amount of network data is subject to analysis.
In general, ever-increasing network speeds often leave traditional hardware running operating systems unable to analyze all, or even a significant amount, of network packets communicated over the network. Further, sometimes the analysis includes determining whether network data matches predefined data (e.g. malware, etc.), such that even when analysis is possible for at least substantially all network data on a network, the analysis is inefficient. Just by way of example, hardware accelerated, pattern matching is usually performed for reporting matches found in a data stream, and many of the matches are oftentimes irrelevant. This therefore creates a large overload of identified matches which require further processing. There is thus a need for addressing these and/or other issues associated with the prior art.